Data Management Plan Database

A Data Management Plan (DMP) describes how you will manage, store, secure, document, and share research data. DMPs can vary broadly across disciplines, methodologies, and data types. DMPs are a growing requirement for grants, and can also guide data practices for individuals and teams. DMP Assistant is a free webtool that guides you through drafting your DMP and the easiest way to start building a DMP.

Our database gathers examples from across the world including DMPs from the Digital Research Alliance of Canada, National Institutes of Health (NIH), Qualitative DMP Competition, DataOne, Digital Curation Centre, Liber, the Working Group on NIH DMSP Guidance, and UC San Diego Research Data Curation into one searchable, open-access platform.

Download the amalgamated dataset: https://doi.org/10.5683/SP3/SDITUG

Project Team: Rebeca Gaston Jothyraj (RDM Assistant - 2024), Shrey Acharya (RDM Assistant - 2023), Sarthak Behal (RDM Assistant 2022-23), Danica Evering and Isaac Pratt (RDM Specialists), Debbie Lawlor (Developer).

Data Management Plan Database

Data Management Plans Overview

Search and Browse Data Management Plans

Displaying 1 - 9 of 9

CAREER: 4.5D Printing of Nickel Titanium Shape Memory Alloys

Original Source

Texas A&M University; Working Group on NIH DMSP Guidance

This DMP outlines a plan for experimental testing, characterization, and simulation data for experiments with nickel-titanium shape memory alloys using a laser powder bed fusion additive manufacturing process. This includes thermal and precipitates evolution physics based modelling.

Clinical Data from Human Research Participants

Original Source

National Institutes of Health (NIH); National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

This is an example of a data management plan from the NIH, intended to collect clinical, demographic, and dialysis data from research participants.

Data Management Plan Template: Systematic Reviews

Original Source

University of Calgary; Digital Research Alliance of Canada

This is a template DMP for use in systematic review projects in any field.

Data Management Plan to Optimize an Industrial Extrusion Process

Original Source

Cégep de Sherbrooke; Digital Research Alliance of Canada

This DMP aims to collect digital, tabular, and graphic data on plastic production parameters, environmental conditions, and inspectional measures among other factors to optimize the industrial extrusion process.

Designing Low-Temperature Synthesis Methods for 2-Dimensional Oxide Perovskites

Original Source

University of Waterloo; Digital Research Alliance of Canada

This DMP aims to collect photographs, Raman data, and lab data to develop new and efficient techniques for synthesizing two-dimensional perovskites at lower temperatures.

EAGER: High-throughput, culture-independent technique identifying cyanobacteria infections to improve understanding of carbon biogeochemical cycling

Original Source

Johns Hopkins University; Working Group on NIH DMSP Guidance

This DMP aims to collect data on viruses and viral infections in the ocean to better understand which bacteria viruses infect. To do this, the researchers are developing a "high-throughput technique to identify cultures in the environment."

Materials Design at the Exascale: European Centre of Excellence in materials modelling, simulations and design

Original Source

MaX Consortium

This DMP was designed for the European Centre of Excellence in materials modeling, simulations and design. It aims to collect code and simulation data.

National Science Foundation (nsf.gov): NSF-ENG: Engineering

Original Source

National Science Foundation (NSF)

This DMP was created by the NSF as a template for Engineering.

SIMPATICO: SIMplifying the interaction with Public Administration Through Information technology for Citizens and cOmpanies

Original Source

Fondazione Bruno Kessler (FBK)

This DMP was created for the SIMPATICO project, which aims to use information technology to improve the experience of citizens and companies in their daily interactions with the public administration. The datasets that will be collected include logging/feedback, citizenpedia, and citizen personal data.